Simon Fraser University

Regression with Autocorrelated Errors

Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...
Simon Fraser University

Input Variables and Regression with ARMA Errors

To use input series, list the input series in a CROSSCORR= option on the IDENTIFY statement and specify how they enter the model with an INPUT= option on the ESTIMATE statement. For example, you might ...
JSTOR Daily

Some Remarks on Regression with Autoregressive Errors and Their Residual Processes

Journal of Applied Probability and Advances in Applied Probability have for four decades provided a forum for original research and reviews in applied probability, mapping the development of ...
JSTOR Daily

Distribution of Residual Autocorrelations in the Regression Model with Autoregressive-Moving Average Errors

This is a preview. Log in through your library . Abstract In examining the adequacy of a statistical model an analysis of the residuals is often carried out; and for models involving a time series ...